add logic kernel for mlu (#39940)

paddle/fluid/operators/controlflow/compare_op_mlu.cc

+/* Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License. */
+
+#include "paddle/fluid/operators/controlflow/compare_op.h"
+#include "paddle/fluid/operators/mlu/mlu_baseop.h"
+
+namespace paddle {
+namespace operators {
+
+template <typename DeviceContext, typename T>
+class EqualMLUKernel : public framework::OpKernel<T> {
+ public:
+  void Compute(const framework::ExecutionContext& ctx) const override {
+    auto* x = ctx.Input<framework::LoDTensor>("X");
+    auto* y = ctx.Input<framework::LoDTensor>("Y");
+    auto* out = ctx.Output<framework::LoDTensor>("Out");
+    out->mutable_data<bool>(ctx.GetPlace());
+
+    MLUCnnlTensorDesc input_x(*x, CNNL_LAYOUT_ARRAY,
+                              ToCnnlDataType(x->dtype()));
+    MLUCnnlTensorDesc input_y(*y, CNNL_LAYOUT_ARRAY,
+                              ToCnnlDataType(y->dtype()));
+    MLUCnnlTensorDesc output(*out, CNNL_LAYOUT_ARRAY,
+                             ToCnnlDataType(out->dtype()));
+    MLUCnnl::Logic(ctx, CNNL_LOGIC_OP_EQ, input_x.get(), GetBasePtr(x),
+                   input_y.get(), GetBasePtr(y), output.get(), GetBasePtr(out));
+  }
+};
+
+template <typename DeviceContext, typename T>
+class NotEqualMLUKernel : public framework::OpKernel<T> {
+ public:
+  void Compute(const framework::ExecutionContext& ctx) const override {
+    auto* x = ctx.Input<framework::LoDTensor>("X");
+    auto* y = ctx.Input<framework::LoDTensor>("Y");
+    auto* out = ctx.Output<framework::LoDTensor>("Out");
+    out->mutable_data<bool>(ctx.GetPlace());
+
+    MLUCnnlTensorDesc input_x(*x, CNNL_LAYOUT_ARRAY,
+                              ToCnnlDataType(x->dtype()));
+    MLUCnnlTensorDesc input_y(*y, CNNL_LAYOUT_ARRAY,
+                              ToCnnlDataType(y->dtype()));
+    MLUCnnlTensorDesc output(*out, CNNL_LAYOUT_ARRAY,
+                             ToCnnlDataType(out->dtype()));
+    MLUCnnl::Logic(ctx, CNNL_LOGIC_OP_NE, input_x.get(), GetBasePtr(x),
+                   input_y.get(), GetBasePtr(y), output.get(), GetBasePtr(out));
+  }
+};
+
+template <typename DeviceContext, typename T>
+class LessThanMLUKernel : public framework::OpKernel<T> {
+ public:
+  void Compute(const framework::ExecutionContext& ctx) const override {
+    auto* x = ctx.Input<framework::LoDTensor>("X");
+    auto* y = ctx.Input<framework::LoDTensor>("Y");
+    auto* out = ctx.Output<framework::LoDTensor>("Out");
+    out->mutable_data<bool>(ctx.GetPlace());
+
+    MLUCnnlTensorDesc input_x(*x, CNNL_LAYOUT_ARRAY,
+                              ToCnnlDataType(x->dtype()));
+    MLUCnnlTensorDesc input_y(*y, CNNL_LAYOUT_ARRAY,
+                              ToCnnlDataType(y->dtype()));
+    MLUCnnlTensorDesc output(*out, CNNL_LAYOUT_ARRAY,
+                             ToCnnlDataType(out->dtype()));
+    MLUCnnl::Logic(ctx, CNNL_LOGIC_OP_LT, input_x.get(), GetBasePtr(x),
+                   input_y.get(), GetBasePtr(y), output.get(), GetBasePtr(out));
+  }
+};
+
+template <typename DeviceContext, typename T>
+class LessEqualMLUKernel : public framework::OpKernel<T> {
+ public:
+  void Compute(const framework::ExecutionContext& ctx) const override {
+    auto* x = ctx.Input<framework::LoDTensor>("X");
+    auto* y = ctx.Input<framework::LoDTensor>("Y");
+    auto* out = ctx.Output<framework::LoDTensor>("Out");
+    out->mutable_data<bool>(ctx.GetPlace());
+
+    MLUCnnlTensorDesc input_x(*x, CNNL_LAYOUT_ARRAY,
+                              ToCnnlDataType(x->dtype()));
+    MLUCnnlTensorDesc input_y(*y, CNNL_LAYOUT_ARRAY,
+                              ToCnnlDataType(y->dtype()));
+    MLUCnnlTensorDesc output(*out, CNNL_LAYOUT_ARRAY,
+                             ToCnnlDataType(out->dtype()));
+    MLUCnnl::Logic(ctx, CNNL_LOGIC_OP_LE, input_x.get(), GetBasePtr(x),
+                   input_y.get(), GetBasePtr(y), output.get(), GetBasePtr(out));
+  }
+};
+
+template <typename DeviceContext, typename T>
+class GreaterThanMLUKernel : public framework::OpKernel<T> {
+ public:
+  void Compute(const framework::ExecutionContext& ctx) const override {
+    auto* x = ctx.Input<framework::LoDTensor>("X");
+    auto* y = ctx.Input<framework::LoDTensor>("Y");
+    auto* out = ctx.Output<framework::LoDTensor>("Out");
+    out->mutable_data<bool>(ctx.GetPlace());
+
+    MLUCnnlTensorDesc input_x(*x, CNNL_LAYOUT_ARRAY,
+                              ToCnnlDataType(x->dtype()));
+    MLUCnnlTensorDesc input_y(*y, CNNL_LAYOUT_ARRAY,
+                              ToCnnlDataType(y->dtype()));
+    MLUCnnlTensorDesc output(*out, CNNL_LAYOUT_ARRAY,
+                             ToCnnlDataType(out->dtype()));
+    MLUCnnl::Logic(ctx, CNNL_LOGIC_OP_GT, input_x.get(), GetBasePtr(x),
+                   input_y.get(), GetBasePtr(y), output.get(), GetBasePtr(out));
+  }
+};
+
+template <typename DeviceContext, typename T>
+class GreaterEqualMLUKernel : public framework::OpKernel<T> {
+ public:
+  void Compute(const framework::ExecutionContext& ctx) const override {
+    auto* x = ctx.Input<framework::LoDTensor>("X");
+    auto* y = ctx.Input<framework::LoDTensor>("Y");
+    auto* out = ctx.Output<framework::LoDTensor>("Out");
+    out->mutable_data<bool>(ctx.GetPlace());
+
+    MLUCnnlTensorDesc input_x(*x, CNNL_LAYOUT_ARRAY,
+                              ToCnnlDataType(x->dtype()));
+    MLUCnnlTensorDesc input_y(*y, CNNL_LAYOUT_ARRAY,
+                              ToCnnlDataType(y->dtype()));
+    MLUCnnlTensorDesc output(*out, CNNL_LAYOUT_ARRAY,
+                             ToCnnlDataType(out->dtype()));
+    MLUCnnl::Logic(ctx, CNNL_LOGIC_OP_GE, input_x.get(), GetBasePtr(x),
+                   input_y.get(), GetBasePtr(y), output.get(), GetBasePtr(out));
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle
+
+namespace ops = paddle::operators;
+namespace plat = paddle::platform;
+
+REGISTER_OP_MLU_KERNEL(
+    equal, ops::EqualMLUKernel<plat::MLUDeviceContext, plat::float16>,
+    ops::EqualMLUKernel<plat::MLUDeviceContext, float>,
+    ops::EqualMLUKernel<plat::MLUDeviceContext, int8_t>,
+    ops::EqualMLUKernel<plat::MLUDeviceContext, uint8_t>,
+    ops::EqualMLUKernel<plat::MLUDeviceContext, int16_t>,
+    ops::EqualMLUKernel<plat::MLUDeviceContext, int>,
+    ops::EqualMLUKernel<plat::MLUDeviceContext, bool>);
+
+REGISTER_OP_MLU_KERNEL(
+    not_equal, ops::NotEqualMLUKernel<plat::MLUDeviceContext, plat::float16>,
+    ops::NotEqualMLUKernel<plat::MLUDeviceContext, float>,
+    ops::NotEqualMLUKernel<plat::MLUDeviceContext, int8_t>,
+    ops::NotEqualMLUKernel<plat::MLUDeviceContext, uint8_t>,
+    ops::NotEqualMLUKernel<plat::MLUDeviceContext, int16_t>,
+    ops::NotEqualMLUKernel<plat::MLUDeviceContext, int>,
+    ops::NotEqualMLUKernel<plat::MLUDeviceContext, bool>);
+
+REGISTER_OP_MLU_KERNEL(
+    less_than, ops::LessThanMLUKernel<plat::MLUDeviceContext, plat::float16>,
+    ops::LessThanMLUKernel<plat::MLUDeviceContext, float>,
+    ops::LessThanMLUKernel<plat::MLUDeviceContext, int8_t>,
+    ops::LessThanMLUKernel<plat::MLUDeviceContext, uint8_t>,
+    ops::LessThanMLUKernel<plat::MLUDeviceContext, int16_t>,
+    ops::LessThanMLUKernel<plat::MLUDeviceContext, int>,
+    ops::LessThanMLUKernel<plat::MLUDeviceContext, bool>);
+
+REGISTER_OP_MLU_KERNEL(
+    less_equal, ops::LessEqualMLUKernel<plat::MLUDeviceContext, plat::float16>,
+    ops::LessEqualMLUKernel<plat::MLUDeviceContext, float>,
+    ops::LessEqualMLUKernel<plat::MLUDeviceContext, int8_t>,
+    ops::LessEqualMLUKernel<plat::MLUDeviceContext, uint8_t>,
+    ops::LessEqualMLUKernel<plat::MLUDeviceContext, int16_t>,
+    ops::LessEqualMLUKernel<plat::MLUDeviceContext, int>,
+    ops::LessEqualMLUKernel<plat::MLUDeviceContext, bool>);
+
+REGISTER_OP_MLU_KERNEL(
+    greater_than,
+    ops::GreaterThanMLUKernel<plat::MLUDeviceContext, plat::float16>,
+    ops::GreaterThanMLUKernel<plat::MLUDeviceContext, float>,
+    ops::GreaterThanMLUKernel<plat::MLUDeviceContext, int8_t>,
+    ops::GreaterThanMLUKernel<plat::MLUDeviceContext, uint8_t>,
+    ops::GreaterThanMLUKernel<plat::MLUDeviceContext, int16_t>,
+    ops::GreaterThanMLUKernel<plat::MLUDeviceContext, int>,
+    ops::GreaterThanMLUKernel<plat::MLUDeviceContext, bool>);
+
+REGISTER_OP_MLU_KERNEL(
+    greater_equal,
+    ops::GreaterEqualMLUKernel<plat::MLUDeviceContext, plat::float16>,
+    ops::GreaterEqualMLUKernel<plat::MLUDeviceContext, float>,
+    ops::GreaterEqualMLUKernel<plat::MLUDeviceContext, int8_t>,
+    ops::GreaterEqualMLUKernel<plat::MLUDeviceContext, uint8_t>,
+    ops::GreaterEqualMLUKernel<plat::MLUDeviceContext, int16_t>,
+    ops::GreaterEqualMLUKernel<plat::MLUDeviceContext, int>,
+    ops::GreaterEqualMLUKernel<plat::MLUDeviceContext, bool>);

python/paddle/fluid/tests/unittests/mlu/test_compare_op_mlu.py

+#  Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from __future__ import print_function
+
+import numpy as np
+import unittest
+import sys
+sys.path.append("..")
+from op_test import OpTest
+import paddle
+import paddle.fluid as fluid
+from paddle.fluid import Program, program_guard
+
+
+def create_test_class(op_type, typename, callback):
+    class Cls(OpTest):
+        def setUp(self):
+            self.set_mlu()
+            self.place = paddle.MLUPlace(0)
+            x = np.random.random(size=(10, 7)).astype(typename)
+            y = np.random.random(size=(10, 7)).astype(typename)
+            out = callback(x, y)
+            self.inputs = {'X': x, 'Y': y}
+            self.outputs = {'Out': out}
+            self.op_type = op_type
+
+        def set_mlu(self):
+            self.__class__.use_mlu = True
+
+        def test_output(self):
+            self.check_output_with_place(place=self.place)
+
+        def test_errors(self):
+            paddle.enable_static()
+            with program_guard(Program(), Program()):
+                a = fluid.layers.data(name='a', shape=[2], dtype='float32')
+                b = fluid.layers.data(name='b', shape=[2], dtype='float32')
+                c = fluid.layers.data(name='c', shape=[2], dtype='int16')
+                d = fluid.create_lod_tensor(np.array([[-1]]), [[1]], self.place)
+
+                op = eval("fluid.layers.%s" % self.op_type)
+                self.assertRaises(TypeError, op, x=a, y=b, axis=True)
+                self.assertRaises(TypeError, op, x=a, y=b, force_cpu=1)
+                self.assertRaises(TypeError, op, x=a, y=b, cond=1)
+                self.assertRaises(TypeError, op, x=a, y=c)
+                self.assertRaises(TypeError, op, x=c, y=a)
+                self.assertRaises(TypeError, op, x=a, y=d)
+                self.assertRaises(TypeError, op, x=d, y=a)
+                self.assertRaises(TypeError, op, x=c, y=d)
+
+        def test_dynamic_api(self):
+            paddle.disable_static()
+            paddle.set_device('mlu:0')
+            x = np.random.random(size=(10, 7)).astype(typename)
+            y = np.random.random(size=(10, 7)).astype(typename)
+            real_result = callback(x, y)
+            x = paddle.to_tensor(x, dtype=typename)
+            y = paddle.to_tensor(y, dtype=typename)
+            op = eval("paddle.%s" % (self.op_type))
+            out = op(x, y)
+            self.assertEqual((out.numpy() == real_result).all(), True)
+
+        @unittest.skipIf(typename == 'float16', "float16 is not supported now")
+        def test_broadcast_api_1(self):
+            paddle.enable_static()
+            with program_guard(Program(), Program()):
+                x = paddle.static.data(
+                    name='x', shape=[1, 2, 1, 3], dtype=typename)
+                y = paddle.static.data(
+                    name='y', shape=[1, 2, 3], dtype=typename)
+                op = eval("paddle.%s" % (self.op_type))
+                out = op(x, y)
+                exe = paddle.static.Executor(self.place)
+                input_x = np.arange(1, 7).reshape((1, 2, 1, 3)).astype(typename)
+                input_y = np.arange(0, 6).reshape((1, 2, 3)).astype(typename)
+                real_result = callback(input_x, input_y)
+                res, = exe.run(feed={"x": input_x,
+                                     "y": input_y},
+                               fetch_list=[out])
+            self.assertEqual((res == real_result).all(), True)
+
+        @unittest.skipIf(typename == 'float16', "float16 is not supported now")
+        def test_broadcast_api_2(self):
+            paddle.enable_static()
+            with program_guard(Program(), Program()):
+                x = paddle.static.data(
+                    name='x', shape=[1, 2, 3], dtype=typename)
+                y = paddle.static.data(
+                    name='y', shape=[1, 2, 1, 3], dtype=typename)
+                op = eval("paddle.%s" % (self.op_type))
+                out = op(x, y)
+                exe = paddle.static.Executor(self.place)
+                input_x = np.arange(0, 6).reshape((1, 2, 3)).astype(typename)
+                input_y = np.arange(1, 7).reshape((1, 2, 1, 3)).astype(typename)
+                real_result = callback(input_x, input_y)
+                res, = exe.run(feed={"x": input_x,
+                                     "y": input_y},
+                               fetch_list=[out])
+            self.assertEqual((res == real_result).all(), True)
+
+        @unittest.skipIf(typename == 'float16', "float16 is not supported now")
+        def test_broadcast_api_3(self):
+            paddle.enable_static()
+            with program_guard(Program(), Program()):
+                x = paddle.static.data(name='x', shape=[5], dtype=typename)
+                y = paddle.static.data(name='y', shape=[3, 1], dtype=typename)
+                op = eval("paddle.%s" % (self.op_type))
+                out = op(x, y)
+                exe = paddle.static.Executor(self.place)
+                input_x = np.arange(0, 5).reshape((5)).astype(typename)
+                input_y = np.array([5, 3, 2]).reshape((3, 1)).astype(typename)
+                real_result = callback(input_x, input_y)
+                res, = exe.run(feed={"x": input_x,
+                                     "y": input_y},
+                               fetch_list=[out])
+            self.assertEqual((res == real_result).all(), True)
+
+        @unittest.skipIf(typename == 'float16', "float16 is not supported now")
+        def test_attr_name(self):
+            paddle.enable_static()
+            with program_guard(Program(), Program()):
+                x = fluid.layers.data(name='x', shape=[4], dtype=typename)
+                y = fluid.layers.data(name='y', shape=[4], dtype=typename)
+                op = eval("paddle.%s" % (self.op_type))
+                out = op(x=x, y=y, name="name_%s" % (self.op_type))
+            self.assertEqual("name_%s" % (self.op_type) in out.name, True)
+
+    cls_name = "{0}_{1}".format(op_type, typename)
+    Cls.__name__ = cls_name
+    globals()[cls_name] = Cls
+
+
+for _type_name in {'float16', 'float32', 'int32', 'bool'}:
+    if _type_name == 'int32' or _type_name == 'bool':
+        create_test_class('equal', _type_name, lambda _a, _b: _a == _b)
+        continue
+    create_test_class('equal', _type_name, lambda _a, _b: _a == _b)
+    create_test_class('not_equal', _type_name, lambda _a, _b: _a != _b)
+    create_test_class('less_than', _type_name, lambda _a, _b: _a < _b)
+    create_test_class('less_equal', _type_name, lambda _a, _b: _a <= _b)
+    create_test_class('greater_than', _type_name, lambda _a, _b: _a > _b)
+    create_test_class('greater_equal', _type_name, lambda _a, _b: _a >= _b)
+
+if __name__ == '__main__':
+    unittest.main()